Big Data Integration and Processing

At the end of the course, you will be able to:
*Retrieve data from example database and big data management systems
*Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications
*Identify when a big data problem needs data integration
*Execute simple big data integration and processing on Hadoop and Spark platforms
This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications.
Hardware Requirements:
(A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size.
Software Requirements:
This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.

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初級

完成時間大約為19 小時

英語（English）

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第 3 門課程（共 6 門）

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初級

初級

完成時間（小時）

完成時間大約為19 小時

建議：7 hours/week...

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英語（English）

字幕：英語（English）

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Welcome to Big Data Integration and Processing

Welcome to the third course in the Big Data Specialization. This week you will be introduced to basic concepts in big data integration and processing. You will be guided through installing the Cloudera VM, downloading the data sets to be used for this course, and learning how to run the Jupyter server. ...

Retrieving Big Data (Part 2)

This module covers the various aspects of data retrieval for NoSQL data, as well as data aggregation and working with data frames. You will be introduced to MongoDB and Aerospike, and you will learn how to use Pandas to retrieve data from them....

講師

關於 加州大学圣地亚哥分校

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

關於 大数据 專項課程

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.
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Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data....